A mathematical model is introduced to describe inference schemes used for the causal attribution of social events. Within this framework research is proposed to (l) examine the order in which causal inference schemes emerge (2) to test a linear model for behavioral attributions and (3) to construct a developmental taxonomy for levels of causal reasoning based on the coordination between attributional (post-dictive) and predictive rules of judgment. Five to twelve year olds, representing the preoperational, concrete operational, and formal operational periods, will be presented with a series of social inference tasks. Each task deals with a behavioral effect and two related causes. In the prediction tasks subjects predict the likelihood of a behavior from knowing the state of two related causes; in the attribution tasks subjects infer the state of a cause from knowing the state of the effect and a second related cause. Analysis of variance and functional measurement techniques will be employed to analyze the data and to interpret the results.